// Strategy example: RSI mean-reversion on hourly BTCUSDT data. // // Goes long when RSI(14) crosses below 30 (oversold), exits when RSI crosses // above 70 (overbought). Position is binary (full-in / full-out), fees are // 0.1% per trade (Binance maker tier), no stop-loss. // // Educational example. NOT a recommended trading strategy in real markets. // The point is to show how Wickra streaming indicators wire up into a complete // signal -> fill -> PnL -> equity loop in a single file. It is the Node // counterpart of `examples/python/strategy_rsi_mean_reversion.py` and the Rust // `examples/rust/src/bin/strategy_rsi_mean_reversion.rs`, and prints the same // summary. // // Build the native binding once, then run it: // // cd bindings/node && npm install && npx napi build --platform --release // cd ../../examples/node && npm install // node strategy_rsi_mean_reversion.js // // Uses the checked-in `examples/data/btcusdt-1h.csv` dataset. const fs = require('node:fs'); const path = require('node:path'); const wickra = require('wickra'); const FEE = 0.001; const RSI_PERIOD = 14; const OVERSOLD = 30.0; const OVERBOUGHT = 70.0; const REQUIRED_COLUMNS = ['timestamp', 'open', 'high', 'low', 'close', 'volume']; const DEFAULT_CSV = path.join(__dirname, '..', 'data', 'btcusdt-1h.csv'); // Parse a plain OHLCV CSV into an array of candle objects. The Wickra CSV // layout is plain numeric — no quoted fields, no embedded commas — so splitting // on `,` is a complete and correct parse for it. function loadCandles(csvPath) { const text = fs.readFileSync(csvPath, 'utf8'); const lines = text.split(/\r?\n/).filter((line) => line.length > 0); if (lines.length === 0) { throw new Error(`${csvPath}: file is empty`); } const header = lines[0].split(',').map((cell) => cell.trim()); const missing = REQUIRED_COLUMNS.filter((col) => !header.includes(col)); if (missing.length > 0) { throw new Error( `${csvPath}: CSV header is missing required column(s): ${missing.join(', ')}; ` + `found: ${header.join(', ')}`, ); } if (lines.length === 1) { throw new Error(`${csvPath}: CSV has a header but no data rows`); } const idx = {}; for (const col of REQUIRED_COLUMNS) idx[col] = header.indexOf(col); const candles = []; for (let row = 1; row < lines.length; row++) { const cells = lines[row].split(','); const candle = {}; for (const col of ['open', 'high', 'low', 'close', 'volume']) { const raw = cells[idx[col]]; const value = raw === undefined ? NaN : Number(raw.trim()); if (raw === undefined || raw.trim() === '' || !Number.isFinite(value)) { throw new Error( `${csvPath}: row ${row + 1} column '${col}' is not numeric: ${JSON.stringify(raw)}`, ); } candle[col] = value; } candles.push(candle); } return candles; } // Forced-sign fixed-point (matches Python's `{:+.Nf}`): the value's own minus is // preserved by toFixed; we only add an explicit '+' for non-negative values. function signed(value, digits) { return (value >= 0 ? '+' : '') + value.toFixed(digits); } function printSummary(name, firstPrice, lastPrice, bars, closedTrades, finalEquity, equityCurve) { const buyHold = lastPrice / firstPrice; const stratReturn = finalEquity - 1.0; const bhReturn = buyHold - 1.0; const wins = closedTrades.filter((r) => r > 0).length; const losses = closedTrades.filter((r) => r < 0).length; const best = closedTrades.length ? Math.max(...closedTrades) : 0.0; const worst = closedTrades.length ? Math.min(...closedTrades) : 0.0; const n = closedTrades.length; const meanRet = n ? closedTrades.reduce((a, r) => a + r, 0) / n : 0.0; const varRet = n > 1 ? closedTrades.reduce((a, r) => a + (r - meanRet) ** 2, 0) / (n - 1) : 0.0; const stddev = Math.sqrt(varRet); const sharpe = varRet > 0 ? meanRet / stddev : 0.0; let peak = equityCurve.length ? equityCurve[0] : 1.0; let maxDd = 0.0; for (const eq of equityCurve) { if (eq > peak) peak = eq; const dd = (peak - eq) / peak; if (dd > maxDd) maxDd = dd; } const label = (s) => s.padEnd(23); console.log(`=== ${name} ===`); console.log(`${label('Bars:')}${bars}`); console.log(`${label('Trades:')}${n} (W${wins} / L${losses})`); console.log(`${label('Strategy return:')}${signed(stratReturn * 100, 2)}%`); console.log(`${label('Buy & Hold return:')}${signed(bhReturn * 100, 2)}%`); console.log(`${label('Excess over BH:')}${signed((stratReturn - bhReturn) * 100, 2)}%`); console.log(`${label('Max drawdown:')}${(maxDd * 100).toFixed(2)}%`); console.log( `${label('Per-trade Sharpe:')}${sharpe.toFixed(2)} ` + `(mean ${signed(meanRet, 4)}, stddev ${stddev.toFixed(4)})`, ); console.log(`${label('Best / worst trade:')}${signed(best * 100, 2)}% / ${signed(worst * 100, 2)}%`); console.log(); console.log( 'NOTE: Educational example — fees, slippage, funding costs and tax effects ' + 'are simplified or omitted. Past performance is not indicative of future results.', ); } function main() { const csvPath = process.argv[2] || DEFAULT_CSV; let candles; try { candles = loadCandles(csvPath); } catch (err) { console.error(`error: ${err.message}`); process.exit(1); } if (candles.length < RSI_PERIOD * 4) { console.error(`error: dataset too small: ${candles.length}`); process.exit(1); } const rsi = new wickra.RSI(RSI_PERIOD); let inPosition = false; let entryPrice = 0.0; const closedTrades = []; let equity = 1.0; const equityCurve = []; for (const c of candles) { const rsiVal = rsi.update(c.close); const price = c.close; const mtm = inPosition ? equity * (price / entryPrice) : equity; equityCurve.push(mtm); if (rsiVal == null) continue; if (!inPosition && rsiVal < OVERSOLD) { entryPrice = price; equity *= 1.0 - FEE; inPosition = true; } else if (inPosition && rsiVal > OVERBOUGHT) { const tradeRet = price / entryPrice - 1.0; closedTrades.push(tradeRet); equity *= (1.0 + tradeRet) * (1.0 - FEE); inPosition = false; } } if (inPosition) { const lastPrice = candles[candles.length - 1].close; const tradeRet = lastPrice / entryPrice - 1.0; closedTrades.push(tradeRet); equity *= (1.0 + tradeRet) * (1.0 - FEE); } printSummary( 'RSI Mean-Reversion (1h, BTCUSDT)', candles[0].close, candles[candles.length - 1].close, candles.length, closedTrades, equity, equityCurve, ); } main();